Recommendation Engines

The best recommendation I can have is my own talents, and the fruits of my own labors, and what others will not do for me, I will try and do for myself.

—18–19th-century scientist John James Audubon

Recommendation engines harness the power of available data on user preferences and item details to offer tailored suggestions. At their core, these engines aim to identify commonalities among various items and understand the dynamics of user-item interactions. Rather than just focusing on products, recommendation systems cast a wider net, considering any type of item – be it a song, a news article, or a product – and tailoring their suggestions accordingly.

This chapter starts by presenting the basics of recommendation engines. Then, it discusses various types of recommendation engines. In the subsequent sections of this chapter, we’ll explore the inner workings of recommendation systems. These systems...